ACTM: API Call Transition Matrix-based Malware Detection Method

V. M. Sruthi, B. Thanudas, S. Sreelal, Abhishek Chakraborty, B. S. Manoj
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引用次数: 3

Abstract

Traditional malware detection techniques, such as signature-based detection and traditional antivirus software, are not beneficial for detecting many recent malware threats. In this paper, we propose a novel malware detection technique, API call transition matrix-based malware detection (ACTM), that efficiently detects malware based on their runtime behavior. We find that the ACTM technique performs better and detects malware with approximately 95.23% accuracy. ACTM can find applications in designing real-time malware detection when an enterprise network security system is concerned.
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基于API调用转换矩阵的恶意软件检测方法
传统的恶意软件检测技术,如基于签名的检测和传统的杀毒软件,已经无法检测到许多最新的恶意软件威胁。本文提出了一种新的恶意软件检测技术——基于API调用转移矩阵的恶意软件检测(ACTM),该技术可以根据恶意软件的运行时行为有效地检测恶意软件。我们发现ACTM技术性能更好,检测恶意软件的准确率约为95.23%。ACTM可以应用于企业网络安全系统的实时恶意软件检测设计。
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